About Open Longevity

Open Longevity is an independent research organization focused on aging, regeneration, and life extension. Our work includes the Open Genes database, peer-reviewed publications, research roadmaps, books, and collaborative research projects.

About the Role

We are looking for a Computational Biology Scientist to help build a new research direction at the intersection of single-cell transcriptomics, multi-omics, and AI.

You will independently analyze biomedical datasets, identify biological patterns, formulate testable hypotheses, and turn the results into reproducible research, scientific publications, and practical insights into aging and age-related diseases.

Responsibilities

• Analyze single-cell, transcriptomic, spatial, and multi-omics datasets.

• Identify biological patterns and formulate testable hypotheses about aging and age-related diseases.

• Select appropriate public and proprietary datasets for hypothesis validation.

• Apply and develop modern bioinformatics, statistical, and AI-based approaches.

• Validate analytical results and critically evaluate outputs produced by AI tools and biological foundation models.

• Build reproducible data-analysis workflows in Python and/or R.

• Review scientific literature and connect analytical findings with existing biological evidence.

• Prepare results, visualizations, and conclusions for scientific publications.

• Contribute to the development of Open Longevity’s computational biology program.

Requirements

• Hands-on experience with scRNA-seq, snRNA-seq, spatial transcriptomics, or other omics data.

• Experience independently completing bioinformatics projects from research question to final results.

• Strong Python and/or R skills.

• Practical experience with modern bioinformatics, statistical analysis, visualization, and reproducible workflow tools.

• Strong understanding of statistics, experimental design, batch effects, data integration, and harmonization.

• Ability to independently review scientific literature, formulate hypotheses, and select appropriate datasets and methods for validation.

• Interest in AI tools, biological foundation models, and agentic workflows, combined with the ability to critically validate their outputs.

• Professional written English.

• Ability to work independently and take ownership of research projects.

Experience preparing scientific publications and working with aging, neuroscience, or age-related disease data will be an advantage.

What We Offer

• Fully remote, full-time contractor position.

• Monthly compensation of USD 2,500.

• Milestone-based bonuses.

• Stable, long-term collaboration.

• Work with public and proprietary biomedical datasets.

• Opportunities to contribute to scientific publications and applied research projects.

• The opportunity to help build the computational biology function and potentially grow into the Head of Computational Biology role.

The initial project will focus on single-cell analysis of aging and neurodegenerative changes in human tissues.

How to Apply

Please send:

• Your CV.

• Links to your GitHub profile or examples of previous projects.

• Links on your Google scholar publications

• Answers to the following questions:

1. Have you independently completed at least two bioinformatics projects from start to finish? Please briefly describe each project and your personal contribution.

2. Which R and Python packages have you used for single-cell analysis, transcriptomics, multi-omics, statistical analysis, data visualization, and reproducible workflows?

3. Have you used AI tools, biological foundation models, or agentic workflows in bioinformatics projects? Please briefly describe your experience and how you validated the results.